Book Image

Cognitive Computing with IBM Watson

By : Rob High, Tanmay Bakshi
Book Image

Cognitive Computing with IBM Watson

By: Rob High, Tanmay Bakshi

Overview of this book

Cognitive computing is rapidly becoming a part of every aspect of our lives through data science, machine learning (ML), and artificial intelligence (AI). It allows computing systems to learn and keep on improving as the amount of data in the system increases. This book introduces you to a whole new paradigm of computing – a paradigm that is totally different from the conventional computing of the Information Age. You will learn the concepts of ML, deep learning (DL), neural networks, and AI with the help of IBM Watson APIs. This book will help you build your own applications to understand, and solve problems, and analyze them as per your needs. You will explore various domains of cognitive computing, such as NLP, voice processing, computer vision, emotion analytics, and conversational systems. Equipped with the knowledge of machine learning concepts, how computers do their magic, and the applications of these concepts, you’ll be able to research and apply cognitive computing in your projects.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Summary


Computer vision has quickly become one of the most common examples of the power of deep learning. There is a plethora of deep learning examples of visual recognition—many of which have a very basic level of accuracy in recognizing objects and classifying. Watson also uses deep learning for its Visual Recognition service. However, IBM has honed these algorithms, combining them with different techniques to produce a service that achieves superb accuracy, which can do so for custom recognition models with less training data, and with less compute time than many of the leading services on the market.

In this chapter, we looked at what Watson's Visual Recognition service can do out the box; how to customize it with your own set of classifiers and training data; and how to program it.

In the next chapter, we will examine the speech recognition service.